Unexpected equipment failures are common in manufacturing plants. The implications from such problems ripple throughout the organization: production lines grind to a halt, supply chains back up, productivity plummets, and customers become irritated. Corporations need to minimize such disruptions, so how can you lower its likelihood?

First, you need to take a close look at your operations. Manufacturing equipment comes in all sizes, forms, and levels of sophistication. Many established plants still have devices with minimal (or no) intelligence. In certain cases, suppliers rely on manual methods to track outages, an approach fraught with limitations.

Sometimes, employees enter incorrect information. Manually recording long stoppages is difficult, and in many cases, suppliers do not track small stops, which could have a significant cumulative impact on manufacturing processes.

Such problems can be avoided. If money is in the budget, businesses should consider replacing their inaccurate manual record keeping with automated downtime tracking solutions.

Creating a More Accurate Picture of Downtime

Manufacturers also need to put thought into how they categorize downtime data. They must outline the root cause of a problem in an understandable and a consistent format. General problem categories, such as electrical, mechanical, and operational, are of some value. More descriptive terms paint a more complete picture, but sometimes they become more difficult to collect and analyze.

Typically, companies examine only the immediate repercussions of downtime. Examples such as how long the device was offline and its impact on the production line. However, such interruptions have a ripple effect and create other challenges in your organization.

To gauge the total cost accurately, a company needs to examine the entire picture of what happens in the enterprise when a system goes down. As they work to get the problem device back up and running, personnel are diverted from their other tasks.

Manufacturers may have to pay its workers for overtime hours, delivery times are pushed back, and workarounds need to be devised by various employees. This information needs to be tracked as well as the time that the system did not work.

Taking Both the Short and Long Term into Account

Tracking downtime costs more completely creates opportunities for both short term and long term system improvements. If they can see real-time status of each machine on production system dashboards, employees can quickly take steps to minimize downtime’s potential damage. In addition, plant devices can be programmed to spur corrective actions. If an assembly line malfunction arises, the system may automatically send an email alert to the floor manager and the Operations Technology team. In some cases, the solution may quickly recommend and implement a solution that mitigates the damage.

In the long term, downtime data becomes the foundation for streamlining manufacturing processes. By understanding operations trends, you can troubleshoot and take steps to prevent recurring problems. The data may illustration that a certain type of machine is breaking down regularly, so the company can take a closer look at it.

Accounting for People Problems

Downtime problems stem from different shortcomings. They may be personnel related. Perhaps downtime is disproportionate and occurs during a specific production shift. A system that tracks downtime fields, like the maintenance shift and geographical location, empowers the maintenance manager so they make better decisions on how to alleviate such problems. The shift problems could be resolved by training the employees so they better understand how to use the plant equipment.

In certain cases, a manufacturing process needs to be tuned. By recording and analyzing the individual steps involved in production machine setup and execution, the team may determine that a device needs a warm up before reaching optimal throughput. They then change their processes to reflect that information.

The plant should strive to become more efficient on an ongoing basis. By collecting downtime data, companies can generate reports that establish performance benchmarks and help them track the progress of their continuous Improvement initiatives.

Improving the Maintenance Process

Downtime data can also help the maintenance team prioritize preventive maintenance and equipment replacements. Statistical analysis, reporting and charting of downtime history reveals patterns in equipment breakdowns. Ideally, the company can analyze manufacturing downtime over a user-selected interval and sorted by various criteria: machine, cell, line, shift or operator. The team takes that data and fine tunes its preventive and remedial efforts.

Tracking downtime has a profound effect on how, when and where maintenance resources are used. Companies can more easily determine when maintenance work needs to be done, so it becomes more flexible, more effective, and less costly. Rather than send service technicians out at set intervals, like every three months, enterprises perform such tasks when needed. As a result, maintenance system efficiency rises.

Companies dread downtime for obvious reasons. However, such problems create opportunities for an organization to better understand and improve its operation. By collecting downtime information, manufacturers are able to streamline their operations, boost system performance, reduce operating costs, and meet production demand more consistently.